From linkedin-commander
Analyze post performance. Compares with baseline, detects patterns, evaluates experiments, analyzes comments, updates ICP. Lifecycle-aware.
How this skill is triggered — by the user, by Claude, or both
Slash command
/linkedin-commander:analyzeThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Analyzes post performance, detects patterns, and sharpens the ICP. Lifecycle-aware: distinguishes Active/Cooling/Archived posts.
Analyzes post performance, detects patterns, and sharpens the ICP. Lifecycle-aware: distinguishes Active/Cooling/Archived posts.
IMPORTANT: Delegate the work to the post-analyzer agent. Do NOTHING yourself — start the agent with the Agent tool and pass the post URN.
/analyze <urn> # Analyze single post
/analyze # All posts that need analysis
/analyze patterns # Pattern refresh only (archived posts)
/analyze icp # ICP sharpening only
| Lifecycle | Analysis Behavior |
|---|---|
| Active (0-7 days) | In data/posts/ — analysis possible, but with caveat "metrics still moving" |
| Cooling (7-14 days) | In data/posts/ — good data basis, snapshot 2-3 available |
| Archived (14+ days) | In data/posts/archive/ — final metrics, best basis for pattern detection |
Pattern refresh uses only archived posts (data/posts/archive/).
post-analyzer agentPost Analysis: "Most SMBs underestimate..."
URN: urn:li:activity:7435982583777169408
Lifecycle: Cooling (Day 9)
Performance (Snapshot 2):
Reactions: 89 (Baseline: 45) → +98%
Comments: 12 (Baseline: 5) → +140%
Impressions: 3,200 (Baseline: 1,800) → +78%
Engagement Rate: 3.2% (Baseline: 2.8%) → +14%
Content Properties:
Hook: Surprising Fact | Format: Text | CTA: Question
Day: Tuesday | Hour: 8 | Length: Medium (780 chars)
Pattern Match:
"Surprising Fact" hook → above average
"Tuesday" posting → confirms pattern
"Personal Reference" → +40% (Low Confidence, n=4)
ICP Insight:
Top Engagers: CTOs (30%), Developers (40%), PMs (20%)
Next snapshot in 5 days (Day 14).
Only on archived posts (data/posts/archive/):
npx claudepluginhub sabania/linkedin-cliAnalyzes engagement patterns in published LinkedIn posts across hooks, content characteristics, topics, and structure to inform content strategy.
Track and analyze content performance across Instagram, YouTube, LinkedIn, Twitter/X, and Reddit using anysite MCP server. Measure engagement, identify top content, and optimize posting strategy.
Captures a read-only snapshot of your LinkedIn post analytics into networking.json. Useful for tracking engagement on your own posts over time.